Conference item
Learning-based homothetic tube MPC
- Abstract:
- In this paper, we study homothetic tube model predictive control (MPC) of discrete-time linear systems subject to bounded additive disturbance and mixed constraints on the state and input. Different from most existing work on robust MPC, we assume that the true disturbance set is unknown but a conservative surrogate is available a priori. Leveraging the real-time data, we develop an online learning algorithm to approximate the true disturbance set. This approximation and the corresponding constraints in the MPC optimisation are updated online using computationally convenient linear programs. We provide statistical gaps between the true and learned disturbance sets, based on which, probabilistic recursive feasibility of homothetic tube MPC problems is discussed. Numerical simulations are provided to demonstrate the efficacy of our proposed algorithm and compare with state-of-the-art MPC algorithms.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 624.7KB, Terms of use)
-
- Publisher copy:
- 10.23919/ECC65951.2025.11187061
Authors
+ Deutsche Forschungsgemeinschaft
More from this funder
- Funder identifier:
- https://ror.org/018mejw64
- Grant:
- EXC 2075 – 390740016
- Programme:
- Excellence Strategy
- Publisher:
- IEEE
- Host title:
- 2025 European Control Conference (ECC)
- Pages:
- 2038-2043
- Publication date:
- 2025-06-24
- Acceptance date:
- 2025-04-11
- Event title:
- 23rd European Control Conference (ECC 2025)
- Event location:
- Thessaloniki, Greece
- Event website:
- https://ecc25.euca-ecc.org/
- Event start date:
- 2025-06-24
- Event end date:
- 2025-06-27
- DOI:
- EISSN:
-
2996-8895
- ISSN:
-
2996-8917
- EISBN:
- 9783907144121
- ISBN:
- 9798331502713
- Language:
-
English
- Keywords:
- Pubs id:
-
2122354
- Local pid:
-
pubs:2122354
- Deposit date:
-
2025-05-08
Terms of use
- Copyright holder:
- European Control Association
- Copyright date:
- 2025
- Rights statement:
- © 2025 EUCA.
- Notes:
- The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
If you are the owner of this record, you can report an update to it here: Report update to this record